In our effort to adapt affymetrix SNP array for studying allele-specific gene expression and epigenetic modifications, we developed analytic methods to extract quantitative allelic specific values. The allele-specific values can enhance our ability to understand the biological processes at the haplotype level for gene expression, chromatin state, DNA methylation, genomic imprinting, X chromosome inactivation, and chromosome copy number alterations. The interpretation of this diverse data, however, requires novel analytical methods. We have focused on developing multivariate analytical methods necessary to extract such signals, as well as mathematical models to describe epigenetic regulation of gene expression. Data analyses and novel analytical methods also provide a focal point for interactions with investigators both within and outside of NCI. Whole-genome association studies of complex human diseases represent a new paradigm in the post-genomic era. We developed a sequential method to identify genetic loci that can predict risk of developing esophageal squamous cell carcinoma (ESCC). First, using the generalized linear model (GLM) with adjustment for potential confounders and multiple comparisons, we identified 37 SNPs associated with disease. Recent follow-up study has validated 4 SNPs in a case-control study involving 600 individuals.